Simple Tool for Aircraft Noise-Reduction Route Design

Jinhua Li∗ Neil Chen † Hok K. Ng ‡ Banavar Sridhar §

The design of arrival and departure routes from an airport has to balance the conflictingrequirements of fuel efficiency, airport capacity utilization and community emission andnoise considerations. The commonly used tools for aircraft noise assessment are the FAA’sIntegrated Noise Model (INM) and Aviation Environmental Design Tool (AEDT). Thesetools are suitable to generate precise noise contours. However, they are harder to use withother tools for route design optimization involving evaluation of a large number of aircrafttrajectories. A simplified aircraft noise computation tool, named AIRNOISE, is developedfor preliminary aircraft noise-reduction route design in this paper. AIRNOISE computesaircraft noise based on the same SAE-AIR-1845 procedures used by INM and AEDT.AIRNOISE does not consider components related to terrain and atmosphere adjustments.As a result, it is not only computationally efficient but also flexible to use for customizedaircraft profiles. The aircraft noise results are compared with the FAA’s AEDT2b and showthat the level of accuracy achieved by AIRNOISE can be used to reduce the number ofroute design options to a small number from a large pool for subsequent accurate analysisby INM.

I. Introduction

NASA is developing air traffic management tools to design safe and efficient aircraft routes while balancingemissions and environmental considerations.1,2, 3 The design of arrival and departure routes from an airporthas to balance the conflicting requirements of fuel efficiency, airport capacity utilization and communityemission and noise considerations. INM (Integrated Noise Model) is a software used by the FAA for airportnoise assessment and regulation. Emission and Dispersion Modeling System (EDMS) is used to assess airportair quality by modeling surface emissions and dispersion. The FAA is leading the development of the AviationEnvironment Design Tool (AEDT) that integrates both INM and EDMS into an integrated tool to study theenvironmental consequence of aviation. These tools are suitable to generate precise noise contours. However,they are harder to use with other tools for route design optimization involving evaluation of a large numberof aircraft trajectories.

Development of environmentally friendly aircraft routes and operations require models of aircraft per-formance, emissions and noise. The Base of Aircraft Data (BADA) is widely used for aircraft performancemodels and the Boeing Fuel Flow Method (BFFM) is used for computing engine emissions of CO, HC,NOX , CO2, H2O and SOx. For aircraft-induced contrail modeling, both German Aerospace Center (DLR)’sContrail Cirrus Prediction Tool (CoCiP)4 and NASA’s Aviation Contrail Simulation Model (ACSM)5 areamong the early attempts to model the full life-cycle of aviation-induced linear contrails and compute thecorresponding radiative forcings for global warming impact.

Figure 1 shows a common flow chart to design the optimal aircraft routes to minimize total fuel con-sumption, emissions, and noise. There is other research related to the design of fuel optimal aircraft routes.Aircraft engine emitted carbon dioxide (CO2) can be easily incorporated into the cost function because itis directly proportional to fuel consumption. Aircraft noise and its impact on residents in the vicinity ofairports have been well studied.6,7 Research has focused on aircraft noise acoustic modeling and aircraftnoise impact assessment and a few studies have focused on designing aircraft routes for airport noise impactreduction.8 However, other work attempted to minimize aviation-induced climate impact. Examples include

∗Research Engineer, Stinger Ghaffarian Technologies, email: jinhua.li@nasa.gov†Research Aerospace Engineer, Aviation Systems Division, NASA Ames Research Center‡Research Scientist, University of California, Santa Cruz§Senior Scientist, NASA Ames Research Center, AIAA fellow

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15th AIAA Aviation Technology, Integration, and Operations Conference

22-26 June 2015, Dallas, TX

AIAA 2015-2598

Copyright © 2015 by the American Institute of Aeronautics and Astronautics, Inc. The U.S. Government has a royalty-free license to exercise all rights under the copyright claimed herein for Governmental purposes. All other rights are reserved by the copyright owner.

AIAA Aviation

designing trans-Atlantic routes to reduce the climate impact due to aircraft greenhouse gas emissions andcontrails,9 and evaluating ozone impact due to aviation nitrogen oxide (NOx) emissions.10

Air trafficuse cases

Flight simulatorData

Pre-process

Environemental assessment tool(e.g. INM/AEDT)

Flight performance

Aircraft route / trajectory redesign

Environment character (Fuel/Emission/Noise)

Figure 1: Flow chart of aircraft route and trajectory design and assessment

Note that in Fig. 1, software such as INM and AEDT are included in the internal parts of the designloop. However, the standalone nature and restrictive format of input aircraft profiles make it difficult tointegrate INM and AEDT with other optimization software.

Figure 2 shows an alternative design flow chart, in which simplified environmental computation modulesare first developed and then integrated into the flight simulation software. The benefits include: (1) improvedcomputational efficiency by only reserving the core computation components for the closed-loop iterativecomputation; (2) access to internal components and intermediate results and acceptance of customizedaircraft profiles (including airspeed and engine thrust) inputs; and (3) pre-screening candidate aircraft routesto reduce the scope of the search space. Finally, designed routes with aircraft performance data are fedinto AEDT and/or INM for environment impact assessment. Aircraft performance, emission, and contrailcomputation modules have been developed and integrated into NASA’s fast-time flight simulation software,Future ATM Concepts Evaluation Tool (FACET), in our previous work.2 This paper focuses on aircraftnoise. The aircraft noise computation method is the standard SAE-AIR-1845 procedures used by INM andAEDT.11 In summary, a simplified noise computation tool based on SAE-AIR-1845 procedures withoutconsidering components related to terrain and atmosphere adjustments is developed in this paper. The noisecomputation tool is integrated with FACET or other flight simulation software for designing noise-reducingaircraft routes.

Air trafficuse cases

Flight simulator (FACET) with simplied env. comp. modules

Data Pre-process

Environemental assessment tool

(INM/AEDT)

Flight peformance and env. character

Environment-friendlyAircraft route / operations

optimization algorithm

Environment character (Fuel/Emission/Noise)

Climate impact model(optional)

Figure 2: Flow chart of environmentally friendly aircraft route and operation design and assessment

The rest of this paper is organized as follows: Section II presents the simplified SAE-AIR-1845 noisecomputation method. Section III compares the results of the simplified model with those of the FAA’saviation environment software AEDT2b. Section IV provides some concluding remarks and further extensionof the paper.

II. Noise Computation Method

Average Day-and-Night Sound Level (DNL) is the most commonly used aircraft noise metric and is usedfor US Federal noise standards. For example, 65decibels (dB) DNL is the federal significance threshold foraircraft noise exposure (refer to the FAA Order 1050.1E). Residences that are exposed to 65dB DNL andabove may qualify to receive federal assistance for noise insulation or other compensation. DNL is calculatedby weighted summation of Sound Exposure Level (SEL) of individual aircraft operation over a 24-hourperiod. The weighting is used to account for lower background noise. The SAE-AIR-1845 noise computationmethod used in this study describes procedures for calculating SEL at ground locations.11 By SAE-AIR-1845 procedures, SEL resulting from an aircraft is computed by adding the base noise of the specific aircraft

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engine type from Noise-Power-Distance (NPD) data tables plus some adjustment terms,12 as follows:

Lae = Lae(P, d) +ADJNF +ADJDUR −ADJLA +ADJDIR (1)

NPD base noise values Lae(P, d) are FAA certified which assume straight overhead flight at a constantspeed of 160knots. Slant distance d is the perpendicular distance from observer to the aircraft route whichconsists of a sequence of linear segments. P is corrected engine net thrust.

There is a set of adjustments to account for variations of the flight relative to the observer. The noisefraction adjustment (ADJNF ) is required because the length of each flight segment is finite which is oppositeto the infinite-length aircraft route assumption used when measuring NPD base noise. A noise durationadjustment term (ADJDUR) is used to account for aircraft speed variation. This adjustment becomes non-zero after 160knots. The noise lateral attenuation adjustment term (ADJLA) is applied when the observeris not directly under the aircraft route as noise would gradually decrease as the observer moves away fromaircraft route. The noise ground-based directivity adjustment term (ADJDIR) deals with special cases whenthe observer is behind the aircraft during the takeoff ground roll.

Figure 3 shows a flow chart describing the process of the noise computation model, named AIRNOISE.The equations for the adjustment terms in Eqn. (1) from the INM technical manual12 are given in theappendix. An accumulated SEL for multiple aircraft route segments is calculated by:

Lae,flt = 10 log10 Eae, Eae =

Nseg∑

i=1

10Lae(i)

10 (2)

where Lae(i) is the SEL of the ith aircraft route segment calculated using Eqn. (1) and Nseg is the totalnumber of aircraft route segments.

Finally, the DNL for all aircraft activities over a 24-hour period is computed by:

Ldn =∑

flti∈day

10Lae,flti

10 +∑

fltj∈night

10Lae,fltj

+10

10 − 49.4 (3)

where daytime operation is defined from 0700 to 2200 and nighttime operation is defined from 2200 to 0700local time. So all nighttime flight operations are penalized by 10db by the definition of DNL.

Since AIRNOISE is a simplified model of INM, the system flow chart is essentially the same by comparingFig. 3 with Fig. 3-1 from the INM7.0 Technical Manual.12 Differences are attributed to some otheradjustment terms for the atmosphere and terrain adjustments that were not included in AIRNOISE. Thoseterms are generally less important compared with the terms that are considered in Eqn. (1).

Equation (1) is only applied for exposure-based sound exposure level computation. Another commonly-used metric is maximum-based sound level, which is computed by:

Lasmx = Lasmx(P, d)−ADJLA +ADJDIR (4)

Lasmx = maxi=1,...,Nseg

(Lasmx(i))) (5)

Comparing Eqns. (1) and (4), the maximum-based sound level does not require duration adjustment andfraction adjustment.

In the rest of this section, key flow chart components in Fig. 3 are discussed. First, Figure 4 displaysNPD data for a few Boeing and Airbus commercial aircraft with a slant range distance setting at d = 1000ftwith various engine-power settings for both standard departure and arrival profiles. Some observations fromFig. 4 are: (1) There are clear separations between newer models and older models, in which NPD data fornewer models are pushed toward the lower right corner of the plots (i.e. newer models generate lesser noiseeven with greater engine-power). This exemplifies the manufacturer’s progress on engine noise reductiontechnology while boosting engine power; (2) Arrival aircraft have less sound exposure variation and absolutesound exposure within operating engine-power range than departure aircraft of the same model. For example,sound exposure variance is 10.3db for departure and 2.5db for arrival for the Boeing 787R. Sound exposurevariance is 9.1db for departure and 1.3db for arrival for the Airbus A380. This indicates that departureaircraft sound exposure is more sensitive to engine-power.

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Input: flight trajectories and performance data

segment geometry computation

NPD interpolation L(p,d)

Exposure based metrics?

Lateral attenuation ADJ_LA

Fraction adjustment ADJ_NF

Duration adjustment ADJ_DUR

Is observer behind takeoff roll segement?

Directivity adjustment ADJ_DIR

Noise computation

Next segment

Yes

Yes

No

No

Figure 3: Flow chart of AIRNOISE model

Second, it is a prerequisite to compute geometric parameters based on aircraft route segment and ob-server positions. Consider a simple case for illustration. Given a departure aircraft route segment ofan Airbus A340-211, where aircraft performance ([Ground distance(ft) (or latitude and longitude), Alti-tude(ft), Speed(knots), Thrust(lb-force)]) are P1 = [5893.2, 741.9, 138.9, 25936.9] at the start point andP2 = [6635.1, 1100.4, 139.1, 25976.4] at the end point. There are 3 cases based on relative position betweenobserver and aircraft route segment: (a) Observer is aside aircraft route segment; (b) Observer is behind air-craft route segment; and (c) Observer is ahead aircraft route segment. Figure 5 shows geometric parametersincluding SLRs (slant range (closest) distance to the flight segment), SLRp (slant range (closest) distanceto the flight path), and β (elevation angle) as well as computed exposure-based sound level using Eqn. (1)and maximum sound level using Eqn. (4) for each case with NPD data tables for the Airbus A340-211. Notethat sound exposure level Lae is almost always greater than maximum sound level Lasmx by their definitions,where maximum sound level is the maximum instantaneous sound pressure and sound exposure level is thesum of sound energy (i.e. square of sound pressure) over the duration of a noise event.

III. Simulation Results

An arrival route and a departure aircraft route for a Boeing 737-300 at San Francisco InternationalAirport are simulated using the FAA’s AEDT2b. Their flight profiles are exported as input to AIRNOISE.

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7.5 8 8.5 9 9.5 10 10.5 11 11.580

85

90

95

100

105

110

115

log(P), P corrected net thrust per engine (lb−force)

soun

d ex

posu

re le

vel (

db)

707−320

727−200

747−400

787−8R

A340−211

A380−841

707−320

727−200

747−400

787−8RA340−211

A380−841

Figure 4: NPD data of selected Boeing 700-series and Airbus 300-series aircraft at 1000ft slant range distancefor standard (black) departure and (blue) arrival profiles.

0 200 400 600 800 1000 1200 1400 1600 1800 20005000

5500

6000

6500

7000

7500

β3=20.0o

receptor 3

β1=26.8o

receptor 1

β2=22.4o

receptor 2

SLRs,1

=2441.1ft

x − lateral distance (feet)

SLRp,2

=SLRs,2

=2206.5ft

SLRs,3

=2169.1ft

SLRp,3

=2060.8ft

SLRp,1

=2422.6ft

P2

P1y

− g

roun

d di

stan

ce (

feet

)

SEL1=81.5dB

MAX1=76.6dB

SEL2=82.6dB

MAX2=77.3dB

SEL3=82.4dB

MAX3=77.9dB

Figure 5: Exposure-based sound level and maximum sound level at observers (receptors) located (red) ahead,(green) aside, and (black) behind a departure aircraft route segment of an Airbus A340. Blue line representsaircraft route starting from P1 to P2. SLRp represents slant range (closest) distance to the flight path, SLRs

represents slant range (closest) distance to the flight segment, and β represents elevation angle.

Figure 6 shows the aircraft profile outputs from AEDT2b. The noise results using AIRNOISE developedin this paper are then compared with those using AEDT2b for validation. Note that neither AEDT2b norAIRNOISE consider surface terrain.

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Figure 6: A Boeing 737-300 (top) arrival and (bottom) departure profiles at San Francisco InternationalAirport

Figures 7 shows noise results using AEDT2b and AIRNOISE at a set of predefined grid points on theground for the single arrival and departure flight operations in Fig. 6. Noise results from AEDT2b andAIRNOISE have the similar contour shape and size. Next, Figure 8 shows the differences by subtracting thenoise values grid by grid between AEDT2b and AIRNOISE for quantitative assessment. The results fromAIRNOISE shows good accuracy compared with the results from AEDT2b as the differences at almost allgrid points are less than 2dB (which is below the 3dB threshold that is considered to be a noticeable changeto the human ear), except in the area near the runway (left areas in Fig. 8) simply because noises resultingfrom the aircraft ground roll and taxi are not accounted for in AIRNOISE. More specifically, the averagedifference is 0.67dB for the arrival profile and 1.0dB for the departure profile excluding the area mainlyimpacted by aircraft ground operations. Finally, a common question is whether the noise difference at anygrid point between AEDT2b and INM will increase proportionally with respect to the total number of flightarrival or departure operations. It can be proved that differences of total SEL at any grid point betweenAIRNOISE and AEDT2b for any N ≥ 1 operations of the same flight profiles are unchanged with the proofprovided in the appendix. This is important because it shows that accuracy of AIRNOISE compared withAEDT2b would not change no matter how many flight operations occur.

IV. Conclusion

A simple aircraft noise computation tool, named AIRNOISE, is developed for aircraft noise-reductionroute design. AIRNOISE is a simplified model of the commonly used aircraft noise assessment software INM

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−122.5 −122.4 −122.3 −122.2 −122.1 −122 −121.9 −121.8

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latit

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Figure 7: Sound exposure level (SEL) computed using AIRNOSIE and the FAA’s AEDT2b for the flightprofiles in Fig. 6: (top left) arrival using AIRNOISE, (top right) arrival using AEDT2b, (bottom left)departure using AIRNOISE, and (bottom right) departure using AEDT2b. The black line represents theaircraft route.

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Figure 8: Sound exposure level (SEL) differences between AEDT2b and AIRNOISE for (left) arrival and(right) departure profiles in Fig. 6. The black line represents the aircraft route.

and AEDT without considering components related to terrain and atmosphere adjustments. AIRNOISE iscomputationally efficient and flexible to use for any customized flight profile inputs with access to interme-diate results for iterative trajectory optimization. The tool can be integrated into flight simulation software

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as a noise computation module for real-time aircraft noise computation. The results from AIRNOISE arecompared with those from the FAA’s AEDT2b for single arrival and departure flight operations and showedreasonable accuracy. The maximum difference of noise results using AEDT2b and AIRNOISE is less than2dB and the average difference is less than 1dB, both of which are less than the 3dB threshold that isconsidered to be a noticeable change by the human ear. We also showed that the accuracy does not changeno matter how many flight operations are considered.

V. Acknowledgments

This paper is dedicated to the memory of Dr. Neil Y. Chen, who passed away on Monday, November3rd, 2014. Dr. Chen was a respected air traffic management researcher, the focal point for internationalcollaborations, and had initially led the autonomous traffic flow management research area. Dr. Chenreceived his Ph.D from UCLA in Mechanical and Aerospace Engineering in 2001. He is survived by his wife,Sue, and his two daughters, Stephanie and Sophia. We will sorely miss Neil, his friendship, and good humor.

Appendix

V.A. Noise adjustment terms

Equations of adjustment terms in Eqn. (1) are listed in this section. They are discussed in more details inINM7.0 Technical Manual.12

1. Lateral attenuation adjustment:

ADJLA = −

[

Eengine(φ) +G(l)Λ(β)

10.86

]

(6)

where φ = β+ ǫ is depression angle, β is elevation angle from observer to aircraft route and ǫ is aircraftbanking angle, l is sideline distance, ie. perpendicular distance from observer to aircraft route groundprojection, and

Eengine(φ) = 10 log10

(

[

0.0039 cos2(φ) + sin2(φ)]0.062

0.8786 sin2(2φ) + cos2(2φ)

)

(7)

G(l) =

{

11.83[1− exp (−0.00274l/3.28)], 0 ≤ l ≤ 3000ft

10.86, l > 3000ft(8)

and

Λ(β) =

10.86, β ≤ 0

1.137− 0.0229 + 9.72 exp (−0.142β), β ≤ 50o

0, 50o < β ≤ 90o(9)

2. Duration adjustment:ADJDUR = 10log(160/V ) (10)

where V is aircraft speed.

3. Fraction adjustment:ADJNF = 10logF12 (11)

where F12 is a function of not only geometric parameters but also NPD base noise for both exposure-based sound level and maximum-based sound level.

4. Directivity adjustment:

ADJDIR =

{

51.44− 1.553θ + 0.015147θ2 − 0.000047173θ3, 90o ≤ θ ≤ 148.4o

339.18− 2.5802θ − 0.0045545θ2 + 0.000044193θ3, 148.4o < θ ≤ 180o(12)

where θ is angle between line connecting observer with aircraft and aircraft ground-roll direction.

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V.B. Proof of noise difference accumulation

Assume the total SEL at a grid point computed using AEDT2b is L1,AEDT2b for a single flight operation andLN,AEDT2b for N ≥ 1 flight operations of the same flight profiles. Similarly, L1,AIRNOISE represents totalSEL at the same grid point for the same single flight operation computed using AIRNOISE and LN,AIRNOISE

for N operations. Let dL1 = L1,AEDT2b −L1,AIRNOISE represent noise difference computed using AEDT2band AIRNOISE. Then we want to prove dLN = dL1.Proof: Let L(1) represent SEL value for the 1-st single flight operation. L1 = L(1) by definition. Then SELvalue of the i-th operation of the same flight profile L(i) = L(1) = L1 for i ≥ N where N is the total numberof operations. By using Eqn. (2), the following equation can be derived:

LN = 10 log(N10L1/10) = 10 log(N) + L1 (13)

So LN,AEDT = 10 log(N)+L1,AEDT and LN,AIRNOISE = 10 log(N)+L1,NOISE using Eqn. (13). Finally,

dLN = LN,AEDT − LN,AIRNOISE

= 10 log(N) + L1,AEDT − (10 log(N) + L1,NOISE)

= L1,AEDT − L1,AIRNOISE

= dL1

This completes the proof. �

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